This paper tests cross hedging performance of the KOSPI 200 stock index futures to hedge the downside risk of the KOSPI, KOSPI 200 and KOSDAQ50 spot market. For this purpose we introduce the minimum variance hedge model, bivariate GARCH(1,1) and EGARCH(1,1) model as hedge models. The main results are as follows; First, we find that the direct hedge performance of KOSPI 200 index futures is better than those of indirect hedge performance. second, in case or cross hedge performance the hedge effect of KOSPI 200 stock index futures market against KOSPI 200 stock index spot market is relatively better than those of KOSPI 200 index futures against KOSPI and KOSDAQ spot position. Third, for the out-sample, hedging effectiveness of the risk-minimization with constant hedge ratios is higher than those of the time varying bivariate GARCH(1,1) and EGARCH(1,1) model. In conclusion, investors are encouraged to use simple risk-minimization model rather than the time varying hedge models like GARCH and EGARCH model to hedge the position of the Korean stock index cash markets.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
/
v.15
no.2
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pp.193-208
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2020
In this study, we investigate the effects of technology innovation investments and employment on credit ratings of very small start-up businesses using the data period of 2009 till 2015 test two hypotheses: asymmetric information hypothesis or competence hypothesis. We use financial and non-financial data of 51,903 observations of 12,028 small businesses from a database of a commercial bank and fixed effects panel models and two-stage instrumental variable models. We find that in the short-run small size startups show lower credit ratings than non-startups, and that both technology innovation activities and employment capability improve their credit ratings. In the long-run, technology innovation investments do not improve their credit ratings of later years while employment capability improve their credit ratings of the subsequent year. In addition, the age of startups improves their credit ratings of the current year and until the subsequent two years while employee productivity, fixed ratio and ROA positively affect their credit ratings for up to three years. However, short-term and overall debt ratios, cost of borrowings and firm-size negatively affect their credit ratings for up to three years. The results of the study on credit ratings suggest that credit rating agencies seem to consider both technology innovation activities and employment capability in the credit ratings of small start-ups as 'competence factors' rather than 'asymmetric information factors' with inefficiency and cost burdens. The results also suggest that we must find ways to reflect properly the severe asymmetric information of the early-stage start-ups, and technology innovation activities and employment capability in the credit rating formula.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.12
no.4
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pp.1-14
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2017
New business management methods different from the past are necessary because of the rapid changes of the corporates' environment. KOSDAQ(Korean Securities Dealers Automated Quotation) companies should be expected the more affirmative business performance of companies by listing, but it is a well-known that they have problems of low business performance mostly. This paper aims to investigate the influential factors on enhancing corporate innovation and nonfinantial business performance, and to clarify practical measures and present a solution of KOSDAQ companies' problems through analysis of previous researches and an empirical research. This research present corporate entrepreneurship and human resources innovation as impact factors on the business performance to apply finely the path of technological innovation for the solution of the relevance investigation limit between the complexity of corporates' innovation paths and the firms' performance. And also knowledge management activities and external networks management or the firms have been adopted as a corporate innovation activities for free from quantitative measures, such as conventional research and development(R&D) activities by considering recent corporates' knowledge business operations. The results of the empirical analysis shows that significant impact factors on corporate innovation activities are the firms' propensities of competitive advantage initiative, risk taking and chief executive officer's innovation. These can be interpreted that the CEOs' innovation propensity should be enhanced for stimulating corporate's innovaton activities, which include the CEOs' interest in the development of new technology, the exploiting new businesses and their support of the innovation discipline for employees. In addition, it can be said that it is necessary to intensify more initiatives within those enterprise for enhancing the competitive advantage in the identical industry. The significant impact factors of corporate entrepreneurship and human resource innovation on the non-financial performance are resulted as the propensities of firms' competitive advantage initiative, CEOs' innovation and employees' innovaton. This shows that the higher propensities of firms' competitive advantage initiative, CEOs' innovation and employees' innovaton, the higher the cognitive degrees of business performance within each corporate, which include the members' awareness about firms' sales growth, market share growth, profit ratio growth, customers' preference and corporates' awareness.
Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.
Korean Journal of Construction Engineering and Management
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v.15
no.5
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pp.94-102
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2014
This study analyzes necessity of expanding construction insurance and estimates required budget. Construction insurance is obliged by National Contract Law and Local Contract Law to protect projet owners and contractors from any unexpected construction risk such as financial losses in construction process. Currently the contracts of design-build and alternate-bid projects as well as PQ project, which are greater than 20 billion won, require the contractors to provide construction insurances in Korea. Insurance premiums are borne by the public project owner. Those contractors whose contract volume is less than 20 billion won burden all risks of projects at their cost. This causes equity problem. Because small-and-medium contractors are discriminated against large contractors since insurance-obliged projects are performed by large contractors and insurance premiums are borne by the public project owner. On the other hands, in all engineering projects, regardless of volume, insurance premiums are borne by the project owner. Therefore current regulation has to be improved, by expanding to all public projects. The average ratio of unobliged projects is 46%, in recent 3 years, prime cost of insurance companies is estimated 0.2%. Moreover considering risks of each construction type, prime cost of unobliged works is estimated as 0.13%. Hence additional necessary budget is estimated to be 2.09 billion won if total volume of public work is 3.5 trillion won. And 2.39 billion won is derived if total volume of public projects is 4 trillion won.
Purpose - The purpose of this study is to analyze the efficiency of retail businesses by dividing domestic retailers into discount stores, super supermarkets (SSMs), and department stores. It suggests retail-business investment strategies by using data environment analysis (DEA) to analyze how input elements such as store area, parking lot area, number of employees, and sales management expenses for the convenience of customers positively affect business performance measurements such as sales and visiting customers per day. Research Design, Data, and Methodology - The DEA model calculates a ratio of the weighted mean of various inputs to the weighted mean of various outputs and measures the efficiency of a specific decision making unit (DMU). The study included 19 companies (five discount store DMUs, ten SSM DMUs, and four department store DMUs). Because the business elements and sizes of retail store DMUs used in this analysis are different, average per-store input and output variables were used. Data were collected from "The Yearbook of Retail Industry in Korea (2012)." DEA analysis was used to determine differences in efficiency among discount stores, SSMs, and department stores in terms of the business elements of each retail business. It was also used to determine what business elements were excessively invested in by comparing and analyzing efficiency by business elements using SPSS software's ANOVA (Analysis of Variance). Results - The CCR and BCC efficiency analysis found that the efficiency of discount stores is low. We believe that the saturation state of discount stores is a major factor. The ANOVA analysis confirms the VRS hypothesis with a statistically significant difference among the three groups, based on an analysis confidence interval of 95%. CRS and SE were not found to be significantly different among the three groups. As for the post hoc test, which concretely shows differences by group, the Scheffe's multiple comparison analysis test found the average differences between group 1 (discount stores) and group 2 (SSM) to be statistically significant. Conclusions - The DEA efficiency analysis implies that investment in input elements, including store area, parking lot area, and sales management expenses, were excessive in the case of discount stores, while SSMs need to invest more in promotion activities such as gifts, events, and coupons for customer management. Department stores have found that small companies invest excessively in input elements. Department stores need to invest in differentiated shopping mall complexes. This study was limited in acquiring statistical data; various input variables which might have shown more secure customer management and promotional expenses could not be applied. As the study was limited in various aspects of the efficiency analyses because financial analyses of the companies and of causal relationships, including satisfaction and loyalty of visiting customers, were not done, these aspects will be examined in the next study.
Political connection are widespread in many countries and are a hot topic in economic research right now. In China, companies are actively forming political connections in several ways. Based on the research model and theoretical analysis, this thesis puts forward the research hypothesis and constructs the research model of political connections and corporate performance using the financial data and corporate governance data of China A-share listed real estate companies in 2010-2014. The thesis mainly analyzes the political association of CEO. For the analysis result, this research uses the univariate regression analysis and multivariate analysis to carry out the robustness test. The empirical study analysis includes three parts: firstly, in Chinese listed real estate enterprises, CEO political connection has a significantly negative correlation with corporate performance. It means real estate enterprises whose CEO has political connections gain a lower performance than other enterprises; Secondly, from the personal characteristics of the CEO, age, sex and education level have positive relationship with the performance of the enterprise, the additional post situation negatively related to the firm's performance; Finally, the firm's scale liquidity ratio and capital asset rario have a negative relationship with corporate performance, and the number of top managers is positively related to corporate performance. This research made a study on the political connection in Chinese real estate industry, which could also provide beneficial references for the development of enterprises in this industry.
The association between accounting earnings and the stock price of an entity is the subject that has been most heavily researched during the past 25 years in accounting literature. Researcher's common finding is that there are positive relationships between accounting earnings and stock prices. However, the explanatory power of accounting earnings which was measured by $R^2$ of regression functions used was rather low. To be connected with these low results, The prior studies propose that there will be additional information, errors in variables. This study investigates empirically determinants of earnings response coefficients(ERCs), which measure the correlation between earnings and stock prices, using earnings level / change, as the dependent variable in the return/earnings regression. Specifically, the thesis tests whether the factors such as earnings persistence, growth, systematic risk, image, information asymmetry and firm size. specially, the determinable variables of ERC are explained in detail. The image / information asymmetry variables are selected to be connected with additional information stand point, The debt / growth variables are selected to be connected with errors in variables. In this study, The sample of firms, listed in Korean Stock Exchange was drawn from the KIS-DATA and was required to meet the following criteria: (1) Annual accounting earnings were available over the 1986-1999 period on the KIS-FAS to allow computation of variables parameter; (2) sufficient return data for estimation of market model parameters were available on the KIS-SMAT month returns: (3) each firm had a fiscal year ending in December throughout the study period. Implementation of these criteria yielded a sample of 1,141 firm-year observation over the 10-year(1990-1999) period. A conventional regression specification would use stock returns(abnormal returns) as a dependent variable and accounting earnings(unexpected earnings) changes interacted with other factors as independent variables. In this study, I examined the relation between other factors and the RRC by using reverse regression. For an empirical test, eight hypotheses(including six lower-hypotheses) were tested. The results of the performed empirical analysis can be summarized as follows; The first, The relationship between persistence of earnings and ERC have significance of each by itself, this result accord with one of the prior studies. The second, The relationship between growth and ERC have not significance. The third, The relationship between image and ERC have significance of each by itself, but a forecast code doesn't present. This fact shows that image cost does not effect on market management share, is used to prevent market occupancy decrease. The fourth, The relationship between information asymmetry variable and ERC have significance of each by. The fifth, The relationship between systematic risk$(\beta)$ and ERC have not significance. The sixth, The relationship between debt ratio and ERC have significance of each by itself, but a forecast code doesn't present. This fact is judged that it is due to the effect of financial leverage effect and a tendency of interest.
Kim, Youngjin;Jung, Goosang;Hwang, Jae-Joon;Lee, Hyun-Soo;Kim, Sun Ah;Kim, Tae-Sung
Journal of Digital Convergence
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v.11
no.5
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pp.159-168
/
2013
This study analyze the business efficiency of securities company based on the 2011 performance of 29 securities firms which engage in domestic investment brokerage by applying a combination model of BSC and DEA. And we evaluate business state focused on efficiency which is based on logical system of BSC as business innovation method. The analysis of result is that companies with high customer efficiency index appeared that business efficiency composite index tended to be higher and we identified that customer perspective have an important factor to calculate business efficiency composite index of korea security company. In addition, based on the results of the efficiency analysis we analyze correlation analysis between traditional financial ratio and business efficiency composite index. We confirmed that company of high business efficiency level in terms of BSC have a good record in terms of profitability. BSC-DEA combination model expect to be utilized in security industry sector as well as other industrial sectors as good business indicator to determine the business efficiency and to be used a model can be evaluated the integrated firm valuation of tangible and intangible assets.
In the Korea stock market, individual investors have perceived stock as short arbitrage investment, not long-term investment strategy. In order to reinforce stock market transparency and soundness, it is important to enforce the measures for stock market management. Especially, stock market event caused by financial policy can be given individual investors negative information regarding a stock trading. Thus, it is a need for investigating whether comprehensive review of listing eligibility is influenced on individual investors' responses and stock behaviors in respect of effectiveness. The purpose of this study to examine the relations between such stock market management and transitional aspect of individual investors' trading types and response on the based of pre- and post-event occurrence. Using an dataset of user's text messages on 9 firms posted on the firm-based social media (i.e., Naver, Daum, Paxnet) over the period 2009 to 2014. And we performed text-clustering and topic modeling according to keywords for classifying into investors group and non-investors groups and two types of investors were categorized depending on main topic transition by event windows in Comprehensive review of listing eligibility. The results indicated that a variety of stockholders existed in the stock. And the ratio of non-investors group was on the decrease, on the other hand, the proportion of investors group veer onto the side of pre-pattern after comprehensive review of listing eligibility. A distinctive feature of our study is to explain the influence of stock market management on response changes of individual investors as well as to categorize in accordance with time progression. Implications an suggestions for future research were also discussed.
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